Title: Optimisation of moving target's low-power and high-precision monitoring with RSSI based on static and dynamic clustering
Authors: Li Jingzhao; Ren Ping; Shi Lingling; Shunxiang Zhang
Addresses: School of Computer Science and Engineering, Anhui University of Science and Technology, No. 168, Shungeng Road, Huainan, 232001, China ' School of Computer Science and Engineering, Anhui University of Science and Technology, No. 168, Shungeng Road, Huainan, 232001, China ' School of Computer Science and Engineering, Anhui University of Science and Technology, No. 168, Shungeng Road, Huainan, 232001, China ' School of Computer Science and Engineering, Anhui University of Science and Technology, No. 168, Shungeng Road, Huainan, 232001, China
Abstract: Independently using the static clustering or the dynamic clustering algorithm can lead to the large amount of transmitted data and high energy consumption. This paper proposes a static and dynamic fusion strategy that includes intelligent selection clustering technology, the sensor node density, the cluster size, etc. Theoretical analysis shows that our fusion strategy can reduce the quantity of data transmission, and decrease the power consumption of the wireless sensor network nodes. Further, we designed an adaptive Kalman filter with the optimisation function. Using the improved Kalman filter algorithm, we establish the moving target monitoring model based on the RSSI and Kalman filter algorithm, and then apply it to the moving targets monitoring in the long narrow environment of higher density of anchor nodes. Simulations and experimental results show that the proposed method significantly improved the monitoring accuracy of the moving targets, as well as the energy consumption of the network.
Keywords: wireless sensor networks; WSNs; static clustering; dynamic clustering; moving targets; Kalman filter; optimisation; energy consumption; precision monitoring; RSSI; sensor node density; cluster size; WSN nodes; target monitoring; simulation.
International Journal of Embedded Systems, 2015 Vol.7 No.3/4, pp.334 - 344
Received: 12 Apr 2014
Accepted: 26 Jul 2014
Published online: 11 Oct 2015 *